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GARCH copula quantile regression model for risk spillover analysis

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  • Tian, Maoxi
  • Ji, Hao

Abstract

To assess risk spillovers, this paper proposes a new GARCH copula quantile regression-based CoVaR model in which the nonlinear tail dependence is allowed to change with risk levels. Based on MSCI index daily data, we investigate the risk spillovers from four financial markets to the financial system of developed market. We find that Germany displays the largest risk spillovers, followed by France, the US and the UK, and that the risk spillovers are much larger during the COVID-19 pandemic than during the periods of the financial crisis and sovereign debt crisis.

Suggested Citation

  • Tian, Maoxi & Ji, Hao, 2022. "GARCH copula quantile regression model for risk spillover analysis," Finance Research Letters, Elsevier, vol. 44(C).
    • Handle: RePEc:eee:finlet:v:44:y:2022:i:c:s1544612321001859
    DOI: 10.1016/j.frl.2021.102104
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    1. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    2. Emmanouil N. Karimalis & Nikos K. Nomikos, 2018. "Measuring systemic risk in the European banking sector: a copula CoVaR approach," The European Journal of Finance, Taylor & Francis Journals, vol. 24(11), pages 944-975, July.
    3. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    4. Eric Bouye & Mark Salmon, 2009. "Dynamic copula quantile regressions and tail area dynamic dependence in Forex markets," The European Journal of Finance, Taylor & Francis Journals, vol. 15(7-8), pages 721-750.
    5. Reboredo, Juan C. & Ugolini, Andrea, 2015. "Systemic risk in European sovereign debt markets: A CoVaR-copula approach," Journal of International Money and Finance, Elsevier, vol. 51(C), pages 214-244.
    6. Ji, Qiang & Bouri, Elie & Roubaud, David & Shahzad, Syed Jawad Hussain, 2018. "Risk spillover between energy and agricultural commodity markets: A dependence-switching CoVaR-copula model," Energy Economics, Elsevier, vol. 75(C), pages 14-27.
    7. Fang, Libing & Chen, Baizhu & Yu, Honghai & Qian, Yichuo, 2018. "Identifying systemic important markets from a global perspective: Using the ADCC ΔCoVaR approach with skewed-t distribution," Finance Research Letters, Elsevier, vol. 24(C), pages 137-144.
    8. Tobias Adrian & Markus K. Brunnermeier, 2016. "CoVaR," American Economic Review, American Economic Association, vol. 106(7), pages 1705-1741, July.
      • Tobias Adrian & Markus K. Brunnermeier, 2008. "CoVaR," Staff Reports 348, Federal Reserve Bank of New York.
      • Tobias Adrian & Markus K. Brunnermeier, 2011. "CoVaR," NBER Working Papers 17454, National Bureau of Economic Research, Inc.
    9. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, September.
    10. Giacomini, Enzo & Härdle, Wolfgang & Spokoiny, Vladimir, 2009. "Inhomogeneous Dependence Modeling with Time-Varying Copulae," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(2), pages 224-234.
    11. Abadie A., 2002. "Bootstrap Tests for Distributional Treatment Effects in Instrumental Variable Models," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 284-292, March.
    12. Reboredo, Juan C. & Rivera-Castro, Miguel A. & Ugolini, Andrea, 2016. "Downside and upside risk spillovers between exchange rates and stock prices," Journal of Banking & Finance, Elsevier, vol. 62(C), pages 76-96.
    13. Huang, Jen-Jsung & Lee, Kuo-Jung & Liang, Hueimei & Lin, Wei-Fu, 2009. "Estimating value at risk of portfolio by conditional copula-GARCH method," Insurance: Mathematics and Economics, Elsevier, vol. 45(3), pages 315-324, December.
    14. Ausin, M. Concepcion & Lopes, Hedibert F., 2010. "Time-varying joint distribution through copulas," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2383-2399, November.
    15. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, May.
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    Cited by:

    1. Tian, Maoxi & El Khoury, Rim & Alshater, Muneer M., 2023. "The nonlinear and negative tail dependence and risk spillovers between foreign exchange and stock markets in emerging economies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    2. Tian, Maoxi & Alshater, Muneer M. & Yoon, Seong-Min, 2022. "Dynamic risk spillovers from oil to stock markets: Fresh evidence from GARCH copula quantile regression-based CoVaR model," Energy Economics, Elsevier, vol. 115(C).
    3. Tian, Maoxi & Guo, Fei & Niu, Rong, 2022. "Risk spillover analysis of China’s financial sectors based on a new GARCH copula quantile regression model," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).

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    More about this item

    Keywords

    Systemic risk spillover; CoVaR; Copula quantile regression model; GARCH copula model;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation

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